g-f(2)188 THE BIG PICTURE OF THE DIGITAL AGE (3/31/2021), MIT SMR, Games, Teams, and Moonshots: Google Cloud’s Will Grannis.

VIRAL KNOWLEDGE: The “genioux facts” knowledge news

Extra-condensed knowledge

In Season 2, Episode 2, of Me, Myself, and AI, Google Cloud’s Will Grannis makes it clear that great ideas don’t only come from the obvious subject-area experts in the room; diverse perspectives, coupled with a codified approach to innovation, lead to the best ideas. 

• The collaboration principles and processes Google Cloud relies on can be applied at other organizations across industries.
• Will leads a team of customer-facing technology leaders who, while tasked with bringing machine learning solutions to market, approach their projects with a user-first mindset, ensuring that they first identify the problem to be solved.
• Will Grannis: Gaming is exciting and it is interesting, but let’s take a foundational element of games: understanding the environment that you’re in and defining the problem you want to solve — what’s the objective function, if you will. 
• That is exactly the same question that every manufacturer, every retailer, every financial services organization asks themselves when they’re first starting to apply machine learning.

Genioux knowledge fact condensed as an image

Condensed knowledge

• CONTEXT
• g-f(2)174 THE BIG PICTURE OF THE DIGITAL AGE (3/20/2021), geniouxfacts, Executive guide of golden knowledge to fire up your unlimited growth.
• g-f(2)163 THE BIG PICTURE OF THE DIGITAL AGE, geniouxfacts, The Current Story Illuminates a Successful Path, 3/10/2021.
• g-f(2)151 The Big Picture of the Digital Transformation, 3/1/2021, geniouxfacts, How To Succeed At Business Digital Transformation.
• g-f(2)153 The Big Picture of Business Artificial Intelligence (3/3/2021) in a Single “g-f KBP” Chart
• So in games, the objective functions tend to be a little bit more fun — it could be an adversarial game, where you’re trying to win and beat others, but those underpinnings of how to win in a game actually are very, very relevant to how you design machine learning in the real world to maximize any other type of objective function that you have.
• So for example, in retail, if you’re trying to decrease the friction of a consumer’s online experience, you actually have some objectives that you’re trying to optimize, and thinking about it like a game is actually a useful construct at the beginning of problem definition: What is it that we really want to achieve?
• And I’ll tell you that, being around AI machine learning now for a couple of decades — when it was cool, when it wasn’t cool — I can tell you that the problem definition and really getting a rich sense of the problem you’re trying to solve is absolutely the No. 1 most important criterion for being successful with AI and machine learning. 

Category 2: The Big Picture of the Digital Age

[genioux fact deduced or extracted from MIT SMR + BCG]

Type of essential knowledge of this “genioux fact”: Essential Deduced and Extracted Knowledge (EDEK).

Type of validity of the "genioux fact". 

• Inherited from sources + Supported by the knowledge of one or more experts.

Authors of the genioux fact

Fernando Machuca

References

Games, Teams, and Moonshots: Google Cloud’s Will Grannis, March 30, 2021, Me, Myself, and AI is a collaborative podcast between MIT Sloan Management Review and Boston Consulting Group, hosted by Sam Ransbotham and Shervin Khodabandeh, MIT Sloan Management Review, MIT SMR. 

ABOUT THE HOSTS

Sam Ransbotham (@ransbotham) is a professor in the information systems department at the Carroll School of Management at Boston College, as well as guest editor for MIT Sloan Management Review’s Artificial Intelligence and Business Strategy Big Ideas initiative. Shervin Khodabandeh is a senior partner and managing director at BCG and the coleader of BCG GAMMA (BCG’s AI practice) in North America. He can be contacted at shervin@bcg.com.

Me, Myself, and AI is a collaborative podcast between MIT Sloan Management Review and Boston Consulting Group, hosted by Sam Ransbotham and Shervin Khodabandeh. Its engineer is David Lishansky, and the coordinating producers are Allison Ryder and Sophie Rüdinger.